The berth allocation problem with mobile quay walls: problem definition,solution procedures,and extensions

The berth allocation problem (BAP), which defines a processing interval and a berth at the quay wall for each ship to be (un-)loaded, is an essential decision problem for efficiently operating a container port. In this paper, we integrate mobile quay walls into the BAP. Mobile quay walls are huge propelled floating platforms, which encase ships moored at the immobile quay and provide additional quay cranes for accelerating container processing. Furthermore, additional ships can be processed at the seaside of the platform, so that scarce berthing space at a terminal is enlarged. We formalize the BAP with mobile quay walls and provide suitable solution procedures.     

A hierarchical expert system for integrated scheduling of ship berthing, discharging and material transport

Abstract: Berthing ships at a port and unloading the stowed materials require a series of scheduling problems: ship berthing, discharging, and material transport. To deal effectively with the scheduling complexity due to mutual interdependence among those problems, this paper proposes a two-level hierarchical architecture for the integrated scheduling of all the activities arising in port. The hierarchical architecture assigns ships to multiple lower level dispatchers, each of which makes its own discharging and material transport schedule independently while satisfying the requirements imposed by the higher level coordinator. If any problem occurs within a dispatcher, the higher level coordinator attempts to resolve the trouble through the coordination of other dispatchers. Based on the hierarchical architecture, a prototype scheduling expert system is developed using G2 for the port scheduling problem at a steelworks. Through the object- oriented interaction of frames, the system is shown to effectively construct integrated schedules from the berth scheduling to the material transport scheduling.     

An adaptive large neighborhood search for the discrete and continuous Berth allocation problem

The Berth Allocation Problem (BAP) consists of assigning ships to berthing positions along a quay in a port. The choice of where and when the ships should move is the main decision to be made in this problem. Considering the berthing positions, there are restrictions related to the water depth and the size of the ships among others. There are also restrictions related to the berthing time of the ships which are modeled as time windows. In this work the ships are represented as rectangles to be placed into a space ×time area, avoiding overlaps and satisfying time window constraints. We consider discrete and continuous models for the BAP and we propose an Adaptive Large Neighborhood Search heuristic to solve the problem. Computational experiments indicate that the proposed algorithm is capable of generating high-quality solutions and outperforms competing algorithms for the same problem. In most cases the improvements are statistically significant.     

Optimization-based decision support system for crew scheduling in the cruise industry

Crew members on cruise ships are hired in a global labor market, and a major cost for cruise lines is moving crew members from their home cities to the cruise ship’s departure port. Complicating the crew scheduling problem is the uncertainty due to no-shows, terminations, and other reasons for crew to terminate their contract prematurely. To address this problem, this paper describes a scheduling system that implements a two-stage planning process that first determines overbooking levels for the number of crew to offer contracts to, and then second, a goal integer programming formulation to minimize the movement cost of assigning crew to ships while maintaining adequate crew levels and a desired crew region composition. We solve actual-sized problems characteristic of the cruise industry in a reasonably short amount of time. Experiments comparing the actual crew movement costs to the system’s projected crew movement costs show that the scheduling system can consistently reduce the movement costs in the range of 9–23%, better maintain desired crew levels, and better maintain desired crew region composition.     

基于蚁群算法的泊位调度优化与仿真

在全球贸易经济聚焦在中国的同时,港口的吞吐能力成为目前港口业的主要矛盾。提高泊位这个环节的运作能力,减少船舶在港时间,增加港口的吞吐能力成为主要研究对象。本文采取仿真模型与优化算法相结合的研究方法,把泊位调度问题转化为旅行商问题,建立了一个泊位岸桥协调调度,通过蚁群算法建立数学模型,使船舶在港时间最短为目标建立函数,求得最佳调度方案。用ProModel建立船舶到港停泊及离港仿真模型。验证泊位调度优化的有效性,以便指导港口实际的泊位调度。     

基于量子遗传混合算法的泊位联合调度

为了提高集装箱港口服务效率,减少船舶服务的拖期费用,针对港口硬件（泊位、拖轮、岸桥）既定条件下的拖轮-泊位联合调度问题,新建了以最小化总体船舶在港时间和总拖期时间为目标的数学模型,设计了一种混合算法进行求解。首先,分析确定了将量子遗传算法（QGA）和禁忌搜索（TS）算法进行串行混合的策略;然后,依据该联合调度问题特点,在解决算法实施中的关键技术问题（染色体结构设计和测量、遗传操作、种群更新等）的同时,采用了动态量子旋转门更新机制;最后,用生产实例验证了算法的可行性及有效性。算法实验结果表明,与人工调度结果相比,混合算法的总体船舶在港时间和总拖期时间分别减少了24%和42.7%;与遗传算法结果相比,分别减少了10.9%和22.5%。所提模型及算法不仅能为港口船舶的入泊、离泊和装卸作业环节提供优化作业方案,而且能增强港口竞争力。     

Model and heuristic for berth allocation in tidal bulk ports with stock level constraints

We consider the problem of allocating berth positions for vessels in tidal bulk port terminals. A berth is defined as a specific location alongside a quay where a ship loader is available for loading or unloading vessels, accommodating only one vessel at a time. In tidal ports, draft conditions depend on high tide conditions, since available depth at low tide is not adequate for the movement of ships. Some port terminals are associated with important transnational enterprises which maintain strong control over the stock level of their goods. Since the stock level sometimes depends on a continuous process of consumption or production of minerals, the decision to load or unload vessels must consider the amount of the bulk cargo stored in the port yards. Therefore, a basic criterion for decision making is to give priority to the vessels related to the most critical mineral stock level. A second basic criterion is to decide what sequence of vessels reduces the overall demurrage within a given planning horizon. This paper presents an integer linear programming model based on the transportation problem to represent the Berth Allocation Problem in Tidal Bulk ports with Stock level conditions (BAPTBS). Problem instances are solved by a commercial solver and by a Simulated Annealing-based algorithm (SA). The SA employs a problem-specific heuristic, becoming a valid alternative for finding out good solutions for difficult instances.     

考虑港口拥堵因素的沿海海运网络优化

沿海运输权制度是沿海运输是否保留给本国船舶或者向外国籍船舶开放的制度。港口拥堵主要发生在海运网络的枢纽港上。通过考虑沿海运输权和港口拥堵对轴辐式海运网络加以优化,以海运网络内货物运输总成本最小化为目标函数,构建一个小规模整数规划模型。从欧亚航线覆盖的主要地区中选取10个港口组成海运网络进行算例分析,并使用CPLEX软件进行求解,研究结果表明,通过考虑枢纽港间货物运输的规模经济效应和产生的拥堵成本,可合理地确定枢纽港的位置;若允许沿海捎带,外资航运企业将会改变货物中转的港口。     

A construction and improvement heuristic for a liquefied natural gas inventory routing problem

We present a large scale ship routing and inventory management problem for a producer and distributor of liquefied natural gas (LNG). The problem contains multiple products, inventory and berth capacity at the loading port and a heterogeneous fleet of ships. The goal is to create an annual delivery program to fulfill the producer’s long-term contracts at minimum cost, while maximizing the revenue from selling LNG in the spot market. To solve this problem we have developed a construction and improvement heuristic (CIH).The CIH is a multi-start local search heuristic that constructs a set of solutions using a greedy insertion procedure. The solutions are then improved using either a first-descent neighborhood search, branch-and-bound on a mathematical formulation, or both. Tests on real-life instances show that the CIH provides good solutions in a short amount of time.     

Knowledge-based approach to the optimal dock arrangement

A problem frequently encountered in ports is the sequencing of waiting ships for berthing to load or unload so that the total demurrage cost incurred is minimized. Here a knowledge-based approach is applied to solve this problem. The constraints of the port and the working rules adopted by the port are expressed as knowledge rules and embedded into the framework of the logic of dock arrangement. With the inference mechanism of a knowledge engineering language OPS5, the best arrangement of the docks can be inferred. Since the operation rules differ from port to port, the problem is confined to the material docks of the China Steel Corporation. A system entitled DOCK is designed to find the best three available alternatives. The idea can be applied and the DOCK system modified for use by other ports.     

双向航道集装箱港口船舶调度优化算法

针对拥有双向航道的集装箱港口中船舶进出港所遇到的会遇和追越等问题,提出了一种重点考虑服务规则的新型船舶调度优化算法。首先,同时考虑双向航道的现实约束和港口夜航的安全规定;然后,构建了以所有船舶在港总等待时间最小为目标的混合整数规划模型来得出最佳的船舶进出港次序;最后,设计了嵌入聚合策略的分支切割算法对模型进行求解。通过数值实验可知,运用嵌入聚合策略的分支切割算法所得结果与下界值的平均相对偏差为2.59%。同时,与模拟退火算法与量子差分进化算法的对比结果表明,所提的分支切割算法所得的目标函数值相较于两个对比算法所得目标函数值分别减少了23.56%和17.17%,验证了该算法的有效性。在用所提算法得到方案的敏感性分析中比较了不同抵港安全时间间隔和船舶类型比例对方案结果的影响,为双向航道集装箱港口的船舶调度优化提供了决策支持。     

A quay crane dynamic scheduling problem by hybrid evolutionary algorithm for berth allocation planning

A considerable growth in worldwide container transportation needs essential optimization of terminal operations. An operation schedule for berth and quay cranes can significantly affect turnaround time of ships, which is an important objective of all schedules in a port. This paper addresses the problem of determining the berthing position and time of each ship as well as the number of quay cranes assigned to each ship. The objective of the problem is to minimize the sum of the handling time, waiting time and the delay time for every ship. We introduce a formulation for the simultaneous berth and quay crane scheduling problem. Next, we combine genetic algorithm with heuristic to find an approximate solution for the problem. Computational experiments show that the proposed approaches are applicable to solve this difficult but essential terminal operation problem.     

基于粒子群算法的供油船调度

供油船调度是港口作业船舶调度中不可或缺的一个环节。根据港口的实际情况,以分析供油船的工作过程和特点为基础,本文提出了一种针对供油船的编码方式,并且将粒子群算法应用到供油船调度系统中。经过多次优化运行,证明优化的结果好于仿真。相比传统的经验调度,采用模型和算法的调度方式能够提高供油船作业的效率。     

Movement Planning in the Presence of Flows

This paper investigates the problem of time-optimum movement planning in two and three dimensions for a point robot which has bounded control velocity through a set of n polygonal regions of given translational flow velocities. This intriguing geometric problem has immediate applications to macro-scale motion planning for ships, submarines, and airplanes in the presence of significant flows of water or air. Also, it is a central motion planning problem for many of the meso-scale and micro-scale robots that have been constructed recently, that have environments with significant flows that affect their movement. In spite of these applications, there is very little literature on this problem, and prior work provided neither an upper bound on its computational complexity nor even a decision algorithm. It can easily be seen that an optimum path for the 2D version of this problem can consist of at least an exponential number of distinct segments through flow regions. We provide the first known computational complexity hardness result for the 3D version of this problem; we show the problem is PSPACE hard. We give the first known decision algorithm for the 2D flow path problem, but this decision algorithm has very high computational complexity. We also give the first known efficient approximation algorithms with bounded error.     

A Combinatorial Benders׳ decomposition for the lock scheduling problem

The Lock Scheduling Problem (LSP) is a combinatorial optimization problem that represents a real challenge for many harbours and waterway operators. The LSP consists of three strongly interconnected subproblems: scheduling lockages, assigning ships to chambers, and positioning the ships inside the chambers. These should be interpreted respectively as a scheduling, an assignment, and a packing problem. By combining the first two problems into a master problem and using the packing problem as a subproblem, a decomposition is achieved that can be solved efficiently by a Combinatorial Benders׳ approach. The master problem is solved first, thereby sequencing the ships into a number of lockages. Next, for each lockage, a packing subproblem is checked for feasibility, possibly returning a number of combinatorial inequalities (cuts) to the master problem. The result is an exact approach to the LSP. Experiments are conducted on a set of instances that were generated in correspondence with real world data. The results indicate that the decomposition approach significantly outperforms other exact approaches presented in the literature, in terms of solution quality and computation time.     

An optimization-based decision support system for ship scheduling

The bulk carriers in the world merchant fleet typically operate full between a loading and discharging port, then run empty until they reach the next loading port. The shipping rates of bulk trades are set on supply/demand bases and fluctuate considerably. Thus the proper scheduling of ships in bulk trade has the great potential of improving the owner's profit and economic performance of shipping. This paper considers an optimization-based Decision Support System for ship scheduling. The typical optimization models for scheduling the ships are briefly reviewed and classified by the underlying idea. Then a prototype MoDiSS(Model-based SS in Ship Scheduling) which is based on a set-packing model has been developed on PC base with proper GUI. The performance of the system has been tested and examined using various ship scheduling scenarios and thereby the effectiveness of the system is validated satisfactorily.     

智能化网络管理工具的设计研究

文中主要研究在当前信息化革命背景下的高效网络管理工具设计。传统的网络管理工具中存在过分依赖预先配置信息,导致维护工作量巨大以及学习理解过于复杂的不足。针对这些问题,文中提出了基于端口扫描和工厂模式的智能化检测方法。并采用这种检测方法设计出一种智能化的网络管理工具。这种工具基于开源平台开发,采用面向对象的设计技术,面对日新月异的网络环境有更好的维护性和扩展空间,明显降低了网络管理人员的工作强度,提高了网络管理的工作效率。     

The Traveling Salesman Problem with Draft Limits

In maritime transportation, routing decisions are sometimes affected by draft limits in ports. The draft of a ship is the distance between the waterline and the bottom of the ship and is a function of the load onboard. Draft limits in ports can thus prevent ships to enter these ports fully loaded and may impose a constraint on the sequence of visits made by a ship. This paper introduces the Traveling Salesman Problem with Draft Limits (TSPDL), which is to determine an optimal sequence of port visits under draft limit constraints. We present two mathematical formulations for the TSPDL, and suggest valid inequalities and strengthened bounds. We also introduce a set of instances based on TSPLIB. A branch-and-cut algorithm is applied on both formulations for all these instances. Computational results show that introducing draft limits make the problem much harder to solve. They also indicate that the proposed valid inequalities and strengthened bounds significantly reduce both the number of branch-and-bound nodes and the solution times.     

Dynamic rolling strategy for multi-vessel quay crane scheduling

This paper focuses on the container loading and unloading problem with dynamic ship arrival times. Using a determined berth plan, in combination with the reality of a container terminal production scheduling environment, this paper proposes a scheduling method for quay cranes that can be used for multiple vessels in a container terminal, based on a dynamic rolling-horizon strategy. The goal of this method is to minimize the operation time of all ships at port and obtain operation equilibrium of quay cranes by establishing a mathematical model and using a genetic algorithm to solve the model. Numerical simulations are applied to calculate the optimal loading and unloading order and the completion time of container tasks on a ship. By comparing this result with the traditional method of quay crane loading and unloading, the paper verifies that the quay crane scheduling method for multiple vessels based on a dynamic rolling-horizon strategy can provide a positive contribution to improve the efficiency of container terminal quay crane loading and unloading and reduce resource wastage.     

基于全卷积神经网络的船舶检测和船牌识别系统

船舶检测与识别对于港口智能监控,实现港口资源的有效管理具有重要意义。由于复杂的船舶轮廓、船牌位置不固定、船牌文本类型复杂多样和船牌文字个数不确定等因素,使得船舶的检测和识别非常具有挑战性。本文提出一种基于全卷积神经网络的船舶检测与识别方法：SDR-FCN。SDR-FCN利用本文提出的船舶检测算法SDNet进行船舶检测定位,然后利用本文提出的船牌文本检测算法PDNet进行船牌文字检测,最后利用具备在线自适应性的分类器OA-Classifier进行船牌分类识别。OA-Classifier综合了AIS（船舶自动识别系统）反馈的信息,提高了分类器的识别精度。实际SDR-FCN部署运行表明,它能够以较高的精度可靠地工作,满足实际应用。